The statement comes from the Education Committee of the New Zealand Statistical Association on September 2 2017, as feedback to the Ministry of Education on their consultation document Strengthening Digital Technologies Hangarau Matihiko in the Curriculum. It will be available on CensusAtSchool for NZ’s statistical education community. For background on the Association and Committee, see http://www.stats.org.nz/ and http://www.stats.org.nz/committees/education.

Data scientists form the second group that the Minister lists in her Foreword to the document that exemplify those for whom creating and developing digital technologies will be a core requirement for success.

The New Zealand Statistical Association through its Education Committee is keen to engage with the working groups on Digital Technologies as they further develop the Digital Technology strand on identifying and exploiting synergies that can advance data science in New Zealand schools.

Many countries are starting to recognise that, in this increasingly data-rich and data-dependent world, their curricula need to do much more to educate students in data science and that this should be done quickly. We are involved in an Australian working group planning for data science as a senior secondary subject in Australia and are in contact with others in the US and UK.

Important elements of data science are already taught in New Zealand’s statistics strand of the Mathematics and Statistics learning area, but equally there are important gaps that could profitably be addressed by learning or practicing computational thinking and coding in the context of solving data science problems. We would very much like to see these become priority contexts particularly over the latter years of secondary school.

Additionally, in contrast to similar digital technology documents from Australia and the US, the consultation document does not give any real visibility to harvesting, manipulating, analysing and visualising data in pursuit of real-world insights, and to the potentials and limitations of data. We think that the NZ digital technology document should include these aspects and we would like to assist with this.

To balance our gentle criticisms, which could be seen as towards the margins of the central push of this curriculum, we find a lot to like in the consultation document. We strongly believe that many more students should learn to think algorithmically, to implement their ideas in computer code, and to gain a propensity to use these skills when faced with new problems. We like the slow build-up in the consultation document of computational thinking skills over time, beginning with hands-on tasks and games before involving computers. Abilities in algorithmic thinking and coding are widely applicable skills that are very important to a modern society. But data science is also important to a modern society and we would like to see the educational advances in the former also foster educational advances in the latter.

As a final side point, because of radical changes when the most recent statistics curriculum content came out we have experience in helping to up-skill a teacher community to teach areas that teachers have not been educated in. Our experiences may be useful to those planning further training for digital technologies.

To reinforce our major point, the Education Committee of the New Zealand Statistical Association is keen to engage with those developing the Digital Technologies strand on aspects that can connect with data science.